The physical sciences community is increasingly taking advantage of the possibilities offered by modern data science to solve problems in experimental chemistry and potentially to change the way we design, conduct and understand results from experiments. Successfully exploiting these opportunities involves considerable challenges. In this Expert Recommendation, we focus on experimental co-design and its importance to experimental chemistry. We provide examples of how data science is changing the way we conduct experiments, and we outline opportunities for further integration of data science and experimental chemistry to advance these fields. Our recommendations include establishing stronger links between chemists and data scientists; developing chemistry-specific data science methods; integrating algorithms, software and hardware to ‘co-design’ chemistry experiments from inception; and combining diverse and disparate data sources into a data network for chemistry research.

物理科学界越来越多地利用现代数据科学提供的可能性来解决实验化学中的问题，并有可能改变我们设计、实施和理解实验结果的方式。成功利用这些机会涉及相当大的挑战。在本专家建议中，我们关注实验协同设计及其对实验化学的重要性。我们提供了数据科学如何改变我们进行实验的方式的例子，我们概述了进一步整合数据科学和实验化学以推进这些领域的机会。我们的建议包括在化学家和数据科学家之间建立更牢固的联系；开发特定于化学的数据科学方法；整合算法，从一开始就“共同设计”化学实验的软件和硬件；将不同的和不同的数据源组合成一个用于化学研究的数据网络。